Attention Model has now become an important concept in neural networks that has been researched within diverse application domains. This survey provides a structured and comprehensive overview of the developments in modeling attention. In particular, we propose a taxonomy which groups existing techniques into coherent categories. We review the different neural architectures in which attention has been incorporated, and also show how attention improves interpretability of neural models. Finally, we discuss some applications in which modeling attention has a significant impact. We hope this survey will provide a succinct introduction to attention models and guide practitioners while developing approaches for their applications.
翻译:关注模式现已成为神经网络中的一个重要概念,已经在不同应用领域进行了研究,该调查对模拟关注方面的动态进行了有条理和全面的概述,特别是,我们建议了一种分类法,将现有技术分为连贯的类别;我们审查了将关注纳入其中的不同神经结构,并表明注意如何改善神经模型的解释性;最后,我们讨论了一些模型关注产生重大影响的应用。我们希望这一调查将简要介绍关注模式,指导从业人员制定应用方法。